This is Ground Truth, a series of interesting conversations with the brightest minds in AI, ML, and data science.

 

This event, hosted in our New York City headquarters and livestreamed on Zoom, will be a fireside chat with Jacopo Tagliabue. He'll be discussing recommender systems as well as his recent research which sits at the intersection of language, learning and retrieval. The event will be hosted by Dr. John Dickerson, Chief Scientist at Arthur.

Date: Thursday, April 20, 2023

Time: Doors open (in-person) at 6:00 PM ET; Zoom livestream begins at 6:30 PM ET

Location: Arthur HQ (166 Crosby St.)

 

This is a hybrid event, so it will also be livestreamed for those who cannot make it
in person. The Zoom link will be sent out closer to the event date.

Jacopo Tagliabue

Educated in several acronyms across the globe (UNISR, SFI, MIT), Jacopo was co-founder and CTO of Tooso, a NLP startup in San Francisco acquired by TSX:CVO. He led Coveo’s A.I. and MLOps roadmap from scale-up to IPO, and built out Coveo Labs, an applied R&D practice rooted in collaboration (Stanford, Outerbounds, Netflix, Farfetch, Microsoft, NVIDIA), open source and open science.

Co-creator of the RecList library for trustworthy evaluation of recommender systems, his research work appeared in venues such as NAACL, RecSys, WWW, SIGIR. While building his new company, he is teaching ML Systems at NYU, which is mostly notable because it is the only job he ever had that his parents understand. Learn more about Jacopo here.

 

John Dickerson

Hosting the event from the Arthur side will be Dr. John Dickerson, Arthur's co-founder and Chief Scientist.

John is also an Associate Professor of Computer Science at the University of Maryland. He works at the intersection of machine learning and economics, with a focus on designing incentives that promote "good" participation in complex systems.

His research centers on solving practical economic problems using techniques from computer science, stochastic optimization, and machine learning. He received his PhD in computer science from Carnegie Mellon University (SCS CSD PhD '16). Learn more about John here.

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